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Record W2006674192 · doi:10.1644/06-mamm-a-177r.1

Geographic Variation in Cranial Morphology of Short-beaked Common Dolphins (Delphinus delphis) from the North Atlantic

2007· article· en· W2006674192 on OpenAlexaboutno aff
Andrew J. Westgate

Bibliographic record

VenueJournal of Mammalogy · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsDelphinus delphisPopulationBiologyGeographyZoologyDemography

Abstract

fetched live from OpenAlex

As part of an examination of the population structure of short-beaked common dolphins (Delphinus delphis) in the North Atlantic, I tested if there were systematic differences in cranial morphology, in relation to geographic location, for common dolphins both within the western North Atlantic (wNA; n = 141) and between the wNA and eastern North Atlantic (eNA; n = 106). Cranial specimens from the wNA were obtained between Nova Scotia, Canada, and Florida. Those from the eNA came from the Irish Sea and the coasts of Ireland and the United Kingdom. A Wilks' λ canonical discriminant analysis (CDA) was performed on the within-groups covariance matrix to test whether significant differences in group centroids (multivariate means) existed between putative population units separately for males and females. In addition, the CDA was used to reclassify each dolphin into a geographic group based on the discriminant function. The CDA of 35 cranial variables found no evidence (males: Wilks' λ = 0.603, P = 0.286; females: Wilks' λ = 0.145, P = 0.08) of population structure below the species level within the wNA. Thus, the 1-population model for this region was supported. CDAs revealed significant differences between the eNA and wNA for both males and females (males: Wilks' λ = 0.371, P < 0.0001; females: Wilks' λ = 0.260, P < 0.0001). Cross-validated reclassification rates for males were 78.8% (eNA) and 87.6% (wNA) and for females were 90.6% (eNA) and 81.4% (wNA). Measurements associated with the rostrum were important discriminating variables that might reflect differences in feeding habits between these areas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.245
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2007
Admission routes1
Has abstractyes

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